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Minadakis N, Kaderli L, Horvath R, Bourgeois Y, Xu W, Thieme M, Woods DP, Roulin AC. Polygenic architecture of flowering time and its relationship with local environments in the grass Brachypodium distachyon. Genetics 2024; 227:iyae042. [PMID: 38504651 PMCID: PMC11075549 DOI: 10.1093/genetics/iyae042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 01/12/2024] [Accepted: 03/07/2024] [Indexed: 03/21/2024] Open
Abstract
Synchronizing the timing of reproduction with the environment is crucial in the wild. Among the multiple mechanisms, annual plants evolved to sense their environment, the requirement of cold-mediated vernalization is a major process that prevents individuals from flowering during winter. In many annual plants including crops, both a long and short vernalization requirement can be observed within species, resulting in so-called early-(spring) and late-(winter) flowering genotypes. Here, using the grass model Brachypodium distachyon, we explored the link between flowering-time-related traits (vernalization requirement and flowering time), environmental variation, and diversity at flowering-time genes by combining measurements under greenhouse and outdoor conditions. These experiments confirmed that B. distachyon natural accessions display large differences regarding vernalization requirements and ultimately flowering time. We underline significant, albeit quantitative effects of current environmental conditions on flowering-time-related traits. While disentangling the confounding effects of population structure on flowering-time-related traits remains challenging, population genomics analyses indicate that well-characterized flowering-time genes may contribute significantly to flowering-time variation and display signs of polygenic selection. Flowering-time genes, however, do not colocalize with genome-wide association peaks obtained with outdoor measurements, suggesting that additional genetic factors contribute to flowering-time variation in the wild. Altogether, our study fosters our understanding of the polygenic architecture of flowering time in a natural grass system and opens new avenues of research to investigate the gene-by-environment interaction at play for this trait.
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Affiliation(s)
- Nikolaos Minadakis
- Department of Plant and Microbial Biology, University of Zürich, Zollikerstr. 107, 8008 Zürich, Switzerland
| | - Lars Kaderli
- Department of Plant and Microbial Biology, University of Zürich, Zollikerstr. 107, 8008 Zürich, Switzerland
| | - Robert Horvath
- Department of Plant and Microbial Biology, University of Zürich, Zollikerstr. 107, 8008 Zürich, Switzerland
| | - Yann Bourgeois
- DIADE, University of Montpellier, CIRAD, IRD, 34 000 Montpellier, France
| | - Wenbo Xu
- Department of Plant and Microbial Biology, University of Zürich, Zollikerstr. 107, 8008 Zürich, Switzerland
| | - Michael Thieme
- Department of Plant and Microbial Biology, University of Zürich, Zollikerstr. 107, 8008 Zürich, Switzerland
| | - Daniel P Woods
- Department of Plant Sciences, University of California-Davis, 104 Robbins Hall, Davis, CA 95616, USA
- Howard Hughes Medical Institute, 4000 Jones Bridge Rd, Chevy Chase, MD 20815, USA
| | - Anne C Roulin
- Department of Plant and Microbial Biology, University of Zürich, Zollikerstr. 107, 8008 Zürich, Switzerland
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2
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Pathan N, Deng WQ, Di Scipio M, Khan M, Mao S, Morton RW, Lali R, Pigeyre M, Chong MR, Paré G. A method to estimate the contribution of rare coding variants to complex trait heritability. Nat Commun 2024; 15:1245. [PMID: 38336875 PMCID: PMC10858280 DOI: 10.1038/s41467-024-45407-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 01/22/2024] [Indexed: 02/12/2024] Open
Abstract
It has been postulated that rare coding variants (RVs; MAF < 0.01) contribute to the "missing" heritability of complex traits. We developed a framework, the Rare variant heritability (RARity) estimator, to assess RV heritability (h2RV) without assuming a particular genetic architecture. We applied RARity to 31 complex traits in the UK Biobank (n = 167,348) and showed that gene-level RV aggregation suffers from 79% (95% CI: 68-93%) loss of h2RV. Using unaggregated variants, 27 traits had h2RV > 5%, with height having the highest h2RV at 21.9% (95% CI: 19.0-24.8%). The total heritability, including common and rare variants, recovered pedigree-based estimates for 11 traits. RARity can estimate gene-level h2RV, enabling the assessment of gene-level characteristics and revealing 11, previously unreported, gene-phenotype relationships. Finally, we demonstrated that in silico pathogenicity prediction (variant-level) and gene-level annotations do not generally enrich for RVs that over-contribute to complex trait variance, and thus, innovative methods are needed to predict RV functionality.
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Affiliation(s)
- Nazia Pathan
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Michael G. DeGroote School of Medicine, Hamilton, Canada
| | - Wei Q Deng
- Peter Boris Centre for Addictions Research, St. Joseph's Healthcare Hamilton, Hamilton, Canada
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Canada
| | - Matteo Di Scipio
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Canada
- Department of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, Canada
| | - Mohammad Khan
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Canada
- Department of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, Canada
| | - Shihong Mao
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Canada
| | - Robert W Morton
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Michael G. DeGroote School of Medicine, Hamilton, Canada
| | - Ricky Lali
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Marie Pigeyre
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Canada
- Department of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, Canada
| | - Michael R Chong
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Michael G. DeGroote School of Medicine, Hamilton, Canada
- Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Canada
| | - Guillaume Paré
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Canada.
- Department of Pathology and Molecular Medicine, McMaster University, Michael G. DeGroote School of Medicine, Hamilton, Canada.
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada.
- Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Canada.
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3
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Yoon JH, Kim S. Learning gene networks under SNP perturbation using SNP and allele-specific expression data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.23.563661. [PMID: 37961468 PMCID: PMC10634764 DOI: 10.1101/2023.10.23.563661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Allele-specific expression quantification from RNA-seq reads provides opportunities to study the control of gene regulatory networks by cis-acting and trans-acting genetic variants. Many existing methods performed a single-gene and single-SNP association analysis to identify expression quantitative trait loci (eQTLs), and placed the eQTLs against known gene networks for functional interpretation. Instead, we view eQTL data as a capture of the effects of perturbation of gene regulatory system by a large number of genetic variants and reconstruct a gene network perturbed by eQTLs. We introduce a statistical framework called CiTruss for simultaneously learning a gene network and cis-acting and trans-acting eQTLs that perturb this network, given population allele-specific expression and SNP data. CiTruss uses a multi-level conditional Gaussian graphical model to model trans-acting eQTLs perturbing the expression of both alleles in gene network at the top level and cis-acting eQTLs perturbing the expression of each allele at the bottom level. We derive a transformation of this model that allows efficient learning for large-scale human data. Our analysis of the GTEx and LG×SM advanced intercross line mouse data for multiple tissue types with CiTruss provides new insights into genetics of gene regulation. CiTruss revealed that gene networks consist of local subnetworks over proximally located genes and global subnetworks over genes scattered across genome, and that several aspects of gene regulation by eQTLs such as the impact of genetic diversity, pleiotropy, tissue-specific gene regulation, and local and long-range linkage disequilibrium among eQTLs can be explained through these local and global subnetworks.
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Affiliation(s)
- Jun Ho Yoon
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, United States of America
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Vinuesa CG, Shen N, Ware T. Genetics of SLE: mechanistic insights from monogenic disease and disease-associated variants. Nat Rev Nephrol 2023; 19:558-572. [PMID: 37438615 DOI: 10.1038/s41581-023-00732-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/25/2023] [Indexed: 07/14/2023]
Abstract
The past few years have provided important insights into the genetic architecture of systemic autoimmunity through aggregation of findings from genome-wide association studies (GWAS) and whole-exome or whole-genome sequencing studies. In the prototypic systemic autoimmune disease systemic lupus erythematosus (SLE), monogenic disease accounts for a small fraction of cases but has been instrumental in the elucidation of disease mechanisms. Defects in the clearance or digestion of extracellular or intracellular DNA or RNA lead to increased sensing of nucleic acids, which can break B cell tolerance and induce the production of type I interferons leading to tissue damage. Current data suggest that multiple GWAS SLE risk alleles act in concert with rare functional variants to promote SLE development. Moreover, introduction of orthologous variant alleles into mice has revealed that pathogenic X-linked dominant and recessive SLE can be caused by novel variants in TLR7 and SAT1, respectively. Such bespoke models of disease help to unravel pathogenic pathways and can be used to test targeted therapies. Cell type-specific expression data revealed that most GWAS SLE risk genes are highly expressed in age-associated B cells (ABCs), which supports the view that ABCs produce lupus autoantibodies and contribute to end-organ damage by persisting in inflamed tissues, including the kidneys. ABCs have thus emerged as key targets of promising precision therapeutics.
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Affiliation(s)
- Carola G Vinuesa
- The Francis Crick Institute, London, UK.
- University College London, London, UK.
- China Australia Centre for Personalized Immunology (CACPI), Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai, China.
| | - Nan Shen
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai, China
- Center for Autoimmune Genomics and Aetiology, Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Paediatrics, University of Cincinnati, Cincinnati, OH, USA
| | - Thuvaraka Ware
- The Francis Crick Institute, London, UK
- University College London, London, UK
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5
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Zhang Z, Li H, Weng H, Zhou G, Chen H, Yang G, Zhang P, Zhang X, Ji Y, Ying K, Liu B, Xu Q, Tang Y, Zhu G, Liu Z, Xia S, Yang X, Dong L, Zhu L, Zeng M, Yuan Y, Yang Y, Zhang N, Xu X, Pang W, Zhang M, Zhang Y, Zhen K, Wang D, Lei J, Wu S, Shu S, Zhang Y, Zhang S, Gao Q, Huang Q, Deng C, Fu X, Chen G, Duan W, Wan J, Xie W, Zhang P, Wang S, Yang P, Zuo X, Zhai Z, Wang C. Genome-wide association analyses identified novel susceptibility loci for pulmonary embolism among Han Chinese population. BMC Med 2023; 21:153. [PMID: 37076872 PMCID: PMC10116678 DOI: 10.1186/s12916-023-02844-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 03/22/2023] [Indexed: 04/21/2023] Open
Abstract
BACKGROUND A large proportion of pulmonary embolism (PE) heritability remains unexplained, particularly among the East Asian (EAS) population. Our study aims to expand the genetic architecture of PE and reveal more genetic determinants in Han Chinese. METHODS We conducted the first genome-wide association study (GWAS) of PE in Han Chinese, then performed the GWAS meta-analysis based on the discovery and replication stages. To validate the effect of the risk allele, qPCR and Western blotting experiments were used to investigate possible changes in gene expression. Mendelian randomization (MR) analysis was employed to implicate pathogenic mechanisms, and a polygenic risk score (PRS) for PE risk prediction was generated. RESULTS After meta-analysis of the discovery dataset (622 cases, 8853 controls) and replication dataset (646 cases, 8810 controls), GWAS identified 3 independent loci associated with PE, including the reported loci FGG rs2066865 (p-value = 3.81 × 10-14), ABO rs582094 (p-value = 1.16 × 10-10) and newly reported locus FABP2 rs1799883 (p-value = 7.59 × 10-17). Previously reported 10 variants were successfully replicated in our cohort. Functional experiments confirmed that FABP2-A163G(rs1799883) promoted the transcription and protein expression of FABP2. Meanwhile, MR analysis revealed that high LDL-C and TC levels were associated with an increased risk of PE. Individuals with the top 10% of PRS had over a fivefold increased risk for PE compared to the general population. CONCLUSIONS We identified FABP2, related to the transport of long-chain fatty acids, contributing to the risk of PE and provided more evidence for the essential role of metabolic pathways in PE development.
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Affiliation(s)
- Zhu Zhang
- Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital; National Center for Respiratory Medicine; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; National Clinical Research Center for Respiratory Diseases, Beijing, 100029, China
| | - Haobo Li
- China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital; National Center for Respiratory Medicine; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; National Clinical Research Center for Respiratory Diseases, Beijing, 100029, China
| | - Haoyi Weng
- Shenzhen WeGene Clinical Laboratory; WeGene, Shenzhen Zaozhidao Technology Co. Ltd; Hunan Provincial Key Lab On Bioinformatics, School of Computer Science and Engineering, Central South University, Shenzhen, 518042, China
| | - Geyu Zhou
- Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, College of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hong Chen
- Department of Pulmonary and Critical Care Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Guoru Yang
- Department of Pulmonary and Critical Care Medicine, Weifang No.2 People's Hospital, Weifang, 261021, China
| | - Ping Zhang
- Department of Pulmonary and Critical Care Medicine, Dongguan People's Hospital, Dongguan, 523059, China
| | - Xiangyan Zhang
- Department of Pulmonary and Critical Care Medicine, Guizhou Provincial People's Hospital, Guiyang, 550002, China
| | - Yingqun Ji
- Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital Affiliated by Tongji University, Shanghai, 200120, China
| | - Kejing Ying
- Department of Respiratory Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310020, China
| | - Bo Liu
- Department of Pulmonary and Critical Care Medicine, Department of Clinical Microbiology, Zibo City Key Laboratory of Respiratory Infection and Clinical Microbiology, Linzi District People's Hospital, Zibo, 255400, China
| | - Qixia Xu
- Department of Pulmonary and Critical Care Medicine, the First Affiliated Hospital of University of Science and Technology of China, Hefei, 230001, China
| | - Yongjun Tang
- Department of Pulmonary and Critical Care Medicine, Xiangya Hospital Central South University, Changsha, 410008, China
| | - Guangfa Zhu
- Department of Pulmonary and Critical Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China
| | - Zhihong Liu
- Fuwai Hospital, Chinese Academy of Medical Science; National Center for Cardiovascular Diseases, Beijing, 100037, China
| | - Shuyue Xia
- Department of Pulmonary and Critical Care Medicine, Central Hospital Affiliated to Shenyang Medical College, Shenyang, 110001, China
| | - Xiaohong Yang
- Department of Pulmonary and Critical Care Medicine, People's Hospital of Xinjiang Uygur Autonomous Region, Xinjiang, 830001, China
| | - Lixia Dong
- Department of Pulmonary and Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, 300050, China
| | - Ling Zhu
- Department of Pulmonary and Critical Care Medicine, Shandong Provincial Hospital, Jinan, 250021, China
| | - Mian Zeng
- Department of Medical Intensive Care Unit, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Yadong Yuan
- Department of Pulmonary and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, 050004, China
| | - Yuanhua Yang
- Department of Pulmonary and Critical Care Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100026, China
| | - Nuofu Zhang
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, 510230, China
| | - Xiaomao Xu
- Department of Pulmonary and Critical Care Medicine, Beijing Hospital, Beijing, 100080, China
| | - Wenyi Pang
- Department of Pulmonary and Critical Care Medicine, Beijing Jishuitan Hospital, Beijing, 100035, China
| | - Meng Zhang
- Department of Pulmonary and Critical Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China
| | - Yu Zhang
- China-Japan Friendship Hospital, Capital Medical University; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital; National Center for Respiratory Medicine; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; National Clinical Research Center for Respiratory Diseases, Beijing, 100029, China
| | - Kaiyuan Zhen
- Institute of Clinical Medical Sciences, China-Japan Friendship Hospital; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital; National Center for Respiratory Medicine; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; National Clinical Research Center for Respiratory Diseases, Beijing, 100029, China
| | - Dingyi Wang
- Institute of Clinical Medical Sciences, China-Japan Friendship Hospital; National Center for Respiratory Medicine; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; National Clinical Research Center for Respiratory Diseases, Beijing, China, 100029
| | - Jieping Lei
- Institute of Clinical Medical Sciences, China-Japan Friendship Hospital; National Center for Respiratory Medicine; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; National Clinical Research Center for Respiratory Diseases, Beijing, China, 100029
| | - Sinan Wu
- Institute of Clinical Medical Sciences, China-Japan Friendship Hospital; National Center for Respiratory Medicine; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; National Clinical Research Center for Respiratory Diseases, Beijing, China, 100029
| | - Shi Shu
- Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital; National Center for Respiratory Medicine; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; National Clinical Research Center for Respiratory Diseases, Beijing, 100029, China
| | - Yunxia Zhang
- Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital; National Center for Respiratory Medicine; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; National Clinical Research Center for Respiratory Diseases, Beijing, 100029, China
| | - Shuai Zhang
- Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital; National Center for Respiratory Medicine; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; National Clinical Research Center for Respiratory Diseases, Beijing, 100029, China
| | - Qian Gao
- Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital; National Center for Respiratory Medicine; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; National Clinical Research Center for Respiratory Diseases, Beijing, 100029, China
| | - Qiang Huang
- Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital; National Center for Respiratory Medicine; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; National Clinical Research Center for Respiratory Diseases, Beijing, 100029, China
| | - Chao Deng
- Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, College of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Xi Fu
- Shenzhen WeGene Clinical Laboratory; WeGene, Shenzhen Zaozhidao Technology Co. Ltd; Hunan Provincial Key Lab On Bioinformatics, School of Computer Science and Engineering, Central South University, Shenzhen, 518042, China
| | - Gang Chen
- Shenzhen WeGene Clinical Laboratory; WeGene, Shenzhen Zaozhidao Technology Co. Ltd; Hunan Provincial Key Lab On Bioinformatics, School of Computer Science and Engineering, Central South University, Shenzhen, 518042, China
| | - Wenxin Duan
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Jun Wan
- Department of Pulmonary and Critical Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China
| | - Wanmu Xie
- Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital; National Center for Respiratory Medicine; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; National Clinical Research Center for Respiratory Diseases, Beijing, 100029, China
| | - Peng Zhang
- Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China
| | - Shengfeng Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Peiran Yang
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Xianbo Zuo
- Department of Dermatology, China-Japan Friendship Hospital, Beijing, China; Department of Pharmacy, China-Japan Friendship Hospital, No. 2, East Yinghua Road, Chaoyang District, Beijing, 100029, China.
| | - Zhenguo Zhai
- Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital; National Center for Respiratory Medicine; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; National Clinical Research Center for Respiratory Diseases, Beijing, 100029, China.
| | - Chen Wang
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.
- National Center for Respiratory Medicine, Beijing, China.
- Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Beijing, China.
- National Clinical Research Center for Respiratory Diseases, Beijing, China.
- Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
- Department of Respiratory Medicine, Capital Medical University, Beijing, China.
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6
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Singhal P, Veturi Y, Dudek SM, Lucas A, Frase A, van Steen K, Schrodi SJ, Fasel D, Weng C, Pendergrass R, Schaid DJ, Kullo IJ, Dikilitas O, Sleiman PMA, Hakonarson H, Moore JH, Williams SM, Ritchie MD, Verma SS. Evidence of epistasis in regions of long-range linkage disequilibrium across five complex diseases in the UK Biobank and eMERGE datasets. Am J Hum Genet 2023; 110:575-591. [PMID: 37028392 PMCID: PMC10119154 DOI: 10.1016/j.ajhg.2023.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 03/07/2023] [Indexed: 04/09/2023] Open
Abstract
Leveraging linkage disequilibrium (LD) patterns as representative of population substructure enables the discovery of additive association signals in genome-wide association studies (GWASs). Standard GWASs are well-powered to interrogate additive models; however, new approaches are required for invesigating other modes of inheritance such as dominance and epistasis. Epistasis, or non-additive interaction between genes, exists across the genome but often goes undetected because of a lack of statistical power. Furthermore, the adoption of LD pruning as customary in standard GWASs excludes detection of sites that are in LD but might underlie the genetic architecture of complex traits. We hypothesize that uncovering long-range interactions between loci with strong LD due to epistatic selection can elucidate genetic mechanisms underlying common diseases. To investigate this hypothesis, we tested for associations between 23 common diseases and 5,625,845 epistatic SNP-SNP pairs (determined by Ohta's D statistics) in long-range LD (>0.25 cM). Across five disease phenotypes, we identified one significant and four near-significant associations that replicated in two large genotype-phenotype datasets (UK Biobank and eMERGE). The genes that were most likely involved in the replicated associations were (1) members of highly conserved gene families with complex roles in multiple pathways, (2) essential genes, and/or (3) genes that were associated in the literature with complex traits that display variable expressivity. These results support the highly pleiotropic and conserved nature of variants in long-range LD under epistatic selection. Our work supports the hypothesis that epistatic interactions regulate diverse clinical mechanisms and might especially be driving factors in conditions with a wide range of phenotypic outcomes.
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Affiliation(s)
- Pankhuri Singhal
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yogasudha Veturi
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Scott M Dudek
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Anastasia Lucas
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alex Frase
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kristel van Steen
- Department of Human Genetics, Katholieke Universiteit Leuven, ON4 Herestraat 49, 3000 Leuven, Belgium
| | - Steven J Schrodi
- Laboratory of Genetics, School of Medicine and Public Health, University of Wisconsin, Madison, WI 53706, USA
| | - David Fasel
- Columbia University, New York, NY 10027, USA
| | | | | | | | | | | | | | - Hakon Hakonarson
- Children's Hospital of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jason H Moore
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Scott M Williams
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Marylyn D Ritchie
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Shefali S Verma
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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7
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Lemos JRN, Baidal DA, Poggioli R, Fuenmayor V, Chavez C, Alvarez A, Ricordi C, Alejandro R. HLA-B Matching Prolongs Allograft Survival in Islet Cell Transplantation. Cell Transplant 2023; 32:9636897231166529. [PMID: 37526141 PMCID: PMC10395153 DOI: 10.1177/09636897231166529] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 03/08/2023] [Accepted: 03/14/2023] [Indexed: 08/02/2023] Open
Abstract
Islet cell transplantation (ITx) is an effective therapeutic approach for selected patients with type 1 diabetes with hypoglycemia unawareness and severe hypoglycemia events. In organ transplantation, human leukocyte antigen (HLA) mismatching between donor and recipient negatively impacts transplant outcomes. We aimed to determine whether HLA matching has an impact on islet allograft survival. Forty-eight patients were followed up after islet transplantation at our institution from 2000 to 2020 in a retrospective cohort. Patients underwent intrahepatic ITx or laparoscopic omental approach. Immunosuppression was dependent upon the protocol. We analyzed HLA data restricted to A, B, and DR loci on allograft survival using survival and subsequent multivariable analyses. Patients were aged 42.8 ± 8.4 years, and 64.3% were female. Diabetes duration was 28.6 ± 11.6 years. Patients matching all three HLA loci presented longer graft survival (P = 0.030). Patients with ≥1 HLA-B matching had longer graft survival compared with zero matching (P = 0.025). The number of HLA-B matching was positively associated with time of graft survival (Spearman's rho = 0.590; P = 0.034). Analyses adjusted for confounders showed that ≥1 matching for HLA-B decreased the risk of allograft failure (P = 0.009). Our data suggest that HLA-B matching between recipients and donors improved islet allograft survival. Matching all three HLA loci (A, B, and DR) was also associated with prolonged islet allograft survival. Prospective studies and a larger sample size are warranted to validate our findings.
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Affiliation(s)
- Joana R. N. Lemos
- Diabetes Research Institute (DRI) and Clinical Cell Transplant Program, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - David A. Baidal
- Diabetes Research Institute (DRI) and Clinical Cell Transplant Program, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Raffaella Poggioli
- Diabetes Research Institute (DRI) and Clinical Cell Transplant Program, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Virginia Fuenmayor
- Diabetes Research Institute (DRI) and Clinical Cell Transplant Program, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Carmen Chavez
- Diabetes Research Institute (DRI) and Clinical Cell Transplant Program, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Ana Alvarez
- Diabetes Research Institute (DRI) and Clinical Cell Transplant Program, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Camillo Ricordi
- Diabetes Research Institute (DRI) and Clinical Cell Transplant Program, Miller School of Medicine, University of Miami, Miami, FL, USA
- Division of Cellular Transplantation, Department of Surgery, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Rodolfo Alejandro
- Diabetes Research Institute (DRI) and Clinical Cell Transplant Program, Miller School of Medicine, University of Miami, Miami, FL, USA
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8
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Charney E. The "Golden Age" of Behavior Genetics? PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2022; 17:1188-1210. [PMID: 35180032 DOI: 10.1177/17456916211041602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The search for genetic risk factors underlying the presumed heritability of all human behavior has unfolded in two phases. The first phase, characterized by candidate-gene-association (CGA) studies, has fallen out of favor in the behavior-genetics community, so much so that it has been referred to as a "cautionary tale." The second and current iteration is characterized by genome-wide association studies (GWASs), single-nucleotide polymorphism (SNP) heritability estimates, and polygenic risk scores. This research is guided by the resurrection of, or reemphasis on, Fisher's "infinite infinitesimal allele" model of the heritability of complex phenotypes, first proposed over 100 years ago. Despite seemingly significant differences between the two iterations, they are united in viewing the discovery of risk alleles underlying heritability as a matter of finding differences in allele frequencies. Many of the infirmities that beset CGA studies persist in the era of GWASs, accompanied by a host of new difficulties due to the human genome's underlying complexities and the limitations of Fisher's model in the postgenomics era.
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Affiliation(s)
- Evan Charney
- The Samuel DuBois Cook Center on Social Equity, Duke University
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9
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Gamache I, Legault MA, Grenier JC, Sanchez R, Rhéaume E, Asgari S, Barhdadi A, Zada YF, Trochet H, Luo Y, Lecca L, Murray M, Raychaudhuri S, Tardif JC, Dubé MP, Hussin J. A sex-specific evolutionary interaction between ADCY9 and CETP. eLife 2021; 10:69198. [PMID: 34609279 PMCID: PMC8594919 DOI: 10.7554/elife.69198] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 10/04/2021] [Indexed: 12/14/2022] Open
Abstract
Pharmacogenomic studies have revealed associations between rs1967309 in the adenylyl cyclase type 9 (ADCY9) gene and clinical responses to the cholesteryl ester transfer protein (CETP) modulator dalcetrapib, however, the mechanism behind this interaction is still unknown. Here, we characterized selective signals at the locus associated with the pharmacogenomic response in human populations and we show that rs1967309 region exhibits signatures of positive selection in several human populations. Furthermore, we identified a variant in CETP, rs158477, which is in long-range linkage disequilibrium with rs1967309 in the Peruvian population. The signal is mainly seen in males, a sex-specific result that is replicated in the LIMAA cohort of over 3400 Peruvians. Analyses of RNA-seq data further suggest an epistatic interaction on CETP expression levels between the two SNPs in multiple tissues, which also differs between males and females. We also detected interaction effects of the two SNPs with sex on cardiovascular phenotypes in the UK Biobank, in line with the sex-specific genotype associations found in Peruvians at these loci. We propose that ADCY9 and CETP coevolved during recent human evolution due to sex-specific selection, which points toward a biological link between dalcetrapib’s pharmacogene ADCY9 and its therapeutic target CETP.
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Affiliation(s)
- Isabel Gamache
- Université de Montréal, Montréal, Canada.,Montreal Heart Institute, Montréal, Canada
| | - Marc-André Legault
- Université de Montréal, Montréal, Canada.,Montreal Heart Institute, Montréal, Canada.,Université de Montréal Beaulieu-Saucier Pharmacogenomics Centre, Montréal, Canada
| | | | | | - Eric Rhéaume
- Université de Montréal, Montréal, Canada.,Montreal Heart Institute, Montréal, Canada
| | - Samira Asgari
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, United States.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States
| | - Amina Barhdadi
- Montreal Heart Institute, Montréal, Canada.,Université de Montréal Beaulieu-Saucier Pharmacogenomics Centre, Montréal, Canada
| | - Yassamin Feroz Zada
- Université de Montréal Beaulieu-Saucier Pharmacogenomics Centre, Montréal, Canada
| | - Holly Trochet
- Université de Montréal, Montréal, Canada.,Montreal Heart Institute, Montréal, Canada
| | - Yang Luo
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, United States.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States
| | - Leonid Lecca
- Socios En Salud, Lima, Peru.,Harvard Medical School, Boston, United States
| | - Megan Murray
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, United States
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, United States.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States.,Centre for Genetics and Genomics Versus Arthritis, Manchester Academic Health Science Centre, University of Manchester, Manchester, United Kingdom.,Department of Biomedical Informatics, Harvard Medical School, Boston, United States.,Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, United States
| | - Jean-Claude Tardif
- Université de Montréal, Montréal, Canada.,Montreal Heart Institute, Montréal, Canada
| | - Marie-Pierre Dubé
- Université de Montréal, Montréal, Canada.,Montreal Heart Institute, Montréal, Canada.,Université de Montréal Beaulieu-Saucier Pharmacogenomics Centre, Montréal, Canada
| | - Julie Hussin
- Université de Montréal, Montréal, Canada.,Montreal Heart Institute, Montréal, Canada
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10
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El Hou A, Rocha D, Venot E, Blanquet V, Philippe R. Long-range linkage disequilibrium in French beef cattle breeds. Genet Sel Evol 2021; 53:63. [PMID: 34301193 PMCID: PMC8306006 DOI: 10.1186/s12711-021-00657-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Accepted: 07/15/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Linkage disequilibrium (LD) is a key parameter to study the history of populations and to identify and fine map quantitative trait loci (QTL) and it has been studied for many years in animal populations. The advent of new genotyping technologies has allowed whole-genome LD studies in most cattle populations. However, to date, long-range LD (LRLD) between distant variants on the genome has not been investigated in detail in cattle. Here, we present the first comprehensive study of LRLD in French beef cattle by analysing data on 672 Charolais (CHA), 462 Limousine (LIM) and 326 Blonde d'Aquitaine (BLA) individuals that were genotyped on the Illumina BovineHD Beadchip. Furthermore, whole-genome LD and haplotype block structure were analysed in these three breeds. RESULTS We computed linkage disequilibrium (r2) values for 5.9, 5.6 and 6.0 billion pairs of SNPs on the 29 autosomes of CHA, LIM and BLA, respectively. Mean r2 values drop to less than 0.1 for distances between SNPs greater than 120 kb. However, for the first time, we detected the existence of LRLD in the three main French beef breeds. In total, 598, 266, and 795 LRLD events (r2 ≥ 0.6) were detected in CHA, LIM and BLA, respectively. Each breed had predominantly population-specific LRLD interactions, although shared LRLD events occurred in a number of regions (55 LRLD events were shared between two breeds and nine between the three breeds). Examples of possible functional gene interactions and QTL co-location were observed with some of these LRLD events, which suggests epistatic selection. CONCLUSIONS We identified long-range linkage disequilibrium for the first time in French beef cattle populations. Epistatic selection may be the main source of the observed LRLD events, but other forces may also be involved. LRLD information should be accounted for in genome-wide association studies.
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Affiliation(s)
- Abdelmajid El Hou
- INRAE, PEIRENE EA7500, USC1061 GAMAA, Université de Limoges, 87060, Limoges, France
| | - Dominique Rocha
- INRAE, AgroParisTech, GABI, Université Paris-Saclay, 78350, Jouy-en-Josas, France
| | - Eric Venot
- INRAE, AgroParisTech, GABI, Université Paris-Saclay, 78350, Jouy-en-Josas, France
| | - Véronique Blanquet
- INRAE, PEIRENE EA7500, USC1061 GAMAA, Université de Limoges, 87060, Limoges, France
| | - Romain Philippe
- INRAE, PEIRENE EA7500, USC1061 GAMAA, Université de Limoges, 87060, Limoges, France.
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11
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Sall S, Thompson W, Santos A, Dwyer DS. Analysis of Major Depression Risk Genes Reveals Evolutionary Conservation, Shared Phenotypes, and Extensive Genetic Interactions. Front Psychiatry 2021; 12:698029. [PMID: 34335334 PMCID: PMC8319724 DOI: 10.3389/fpsyt.2021.698029] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 06/21/2021] [Indexed: 12/29/2022] Open
Abstract
Major depressive disorder (MDD) affects around 15% of the population at some stage in their lifetime. It can be gravely disabling and it is associated with increased risk of suicide. Genetics play an important role; however, there are additional environmental contributions to the pathogenesis. A number of possible risk genes that increase liability for developing symptoms of MDD have been identified in genome-wide association studies (GWAS). The goal of this study was to characterize the MDD risk genes with respect to the degree of evolutionary conservation in simpler model organisms such as Caenorhabditis elegans and zebrafish, the phenotypes associated with variation in these genes and the extent of network connectivity. The MDD risk genes showed higher conservation in C. elegans and zebrafish than genome-to-genome comparisons. In addition, there were recurring themes among the phenotypes associated with variation of these risk genes in C. elegans. The phenotype analysis revealed enrichment for essential genes with pleiotropic effects. Moreover, the MDD risk genes participated in more interactions with each other than did randomly-selected genes from similar-sized gene sets. Syntenic blocks of risk genes with common functional activities were also identified. By characterizing evolutionarily-conserved counterparts to the MDD risk genes, we have gained new insights into pathogenetic processes relevant to the emergence of depressive symptoms in man.
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Affiliation(s)
- Saveen Sall
- Department of Psychiatry and Behavioral Medicine, Louisiana State University Health Shreveport, Shreveport, LA, United States
| | - Willie Thompson
- Department of Psychiatry and Behavioral Medicine, Louisiana State University Health Shreveport, Shreveport, LA, United States
| | - Aurianna Santos
- Department of Psychiatry and Behavioral Medicine, Louisiana State University Health Shreveport, Shreveport, LA, United States
| | - Donard S. Dwyer
- Department of Psychiatry and Behavioral Medicine, Louisiana State University Health Shreveport, Shreveport, LA, United States
- Department of Pharmacology, Toxicology and Neuroscience, Louisiana State University Health Shreveport, Shreveport, LA, United States
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12
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Kulski JK, Suzuki S, Shiina T. Haplotype Shuffling and Dimorphic Transposable Elements in the Human Extended Major Histocompatibility Complex Class II Region. Front Genet 2021; 12:665899. [PMID: 34122517 PMCID: PMC8193847 DOI: 10.3389/fgene.2021.665899] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 04/12/2021] [Indexed: 12/26/2022] Open
Abstract
The major histocompatibility complex (MHC) on chromosome 6p21 is one of the most single-nucleotide polymorphism (SNP)-dense regions of the human genome and a prime model for the study and understanding of conserved sequence polymorphisms and structural diversity of ancestral haplotypes/conserved extended haplotypes. This study aimed to follow up on a previous analysis of the MHC class I region by using the same set of 95 MHC haplotype sequences downloaded from a publicly available BioProject database at the National Center for Biotechnology Information to identify and characterize the polymorphic human leukocyte antigen (HLA)-class II genes, the MTCO3P1 pseudogene alleles, the indels of transposable elements as haplotypic lineage markers, and SNP-density crossover (XO) loci at haplotype junctions in DNA sequence alignments of different haplotypes across the extended class II region (∼1 Mb) from the telomeric PRRT1 gene in class III to the COL11A2 gene at the centromeric end of class II. We identified 42 haplotypic indels (20 Alu, 7 SVA, 13 LTR or MERs, and 2 indels composed of a mosaic of different transposable elements) linked to particular HLA-class II alleles. Comparative sequence analyses of 136 haplotype pairs revealed 98 unique XO sites between SNP-poor and SNP-rich genomic segments with considerable haplotype shuffling located in the proximity of putative recombination hotspots. The majority of XO sites occurred across various regions including in the vicinity of MTCO3P1 between HLA-DQB1 and HLA-DQB3, between HLA-DQB2 and HLA-DOB, between DOB and TAP2, and between HLA-DOA and HLA-DPA1, where most XOs were within a HERVK22 sequence. We also determined the genomic positions of the PRDM9-recombination suppression sequence motif ATCCATG/CATGGAT and the PRDM9 recombination activation partial binding motif CCTCCCCT/AGGGGAG in the class II region of the human reference genome (NC_ 000006) relative to published meiotic recombination positions. Both the recombination and anti-recombination PRDM9 binding motifs were widely distributed throughout the class II genomic regions with 50% or more found within repeat elements; the anti-recombination motifs were found mostly in L1 fragmented repeats. This study shows substantial haplotype shuffling between different polymorphic blocks and confirms the presence of numerous putative ancestral recombination sites across the class II region between various HLA class II genes.
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Affiliation(s)
- Jerzy K Kulski
- Faculty of Health and Medical Sciences, The University of Western Australia, Crawley, WA, Australia.,Department of Molecular Life Sciences, Division of Basic Medical Science and Molecular Medicine, Tokai University School of Medicine, Isehara, Japan
| | - Shingo Suzuki
- Department of Molecular Life Sciences, Division of Basic Medical Science and Molecular Medicine, Tokai University School of Medicine, Isehara, Japan
| | - Takashi Shiina
- Department of Molecular Life Sciences, Division of Basic Medical Science and Molecular Medicine, Tokai University School of Medicine, Isehara, Japan
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13
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Fabbri MC, Dadousis C, Bozzi R. Estimation of Linkage Disequilibrium and Effective Population Size in Three Italian Autochthonous Beef Breeds. Animals (Basel) 2020; 10:ani10061034. [PMID: 32545850 PMCID: PMC7341513 DOI: 10.3390/ani10061034] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 06/09/2020] [Accepted: 06/11/2020] [Indexed: 12/13/2022] Open
Abstract
The objective was to investigate the pattern of linkage disequilibrium (LD) in three local beef breeds, namely, Calvana (n = 174), Mucca Pisana (n = 270), and Pontremolese (n = 44). As a control group, samples of the Italian Limousin breed (n = 100) were used. All cattle were genotyped with the GeneSeek GGP-LDv4 33k SNP chip containing 30,111 SNPs. The genotype quality control for each breed was conducted separately, and SNPs with call rate < 0.95 and minor allele frequency (MAF) > 1% were used for the analysis. LD extent was estimated in PLINK v1.9 using the squared correlation between pairs of loci (r2) across autosomes. Moreover, r2 values were used to calculate historical and contemporary effective population size (Ne) in each breed. Average r2 was similar in Calvana and Mucca Pisana (~0.14) and higher in Pontremolese (0.17); Limousin presented the lowest LD extent (0.07). LD up to 0.11-0.15 was persistent in the local breeds up to 0.75 Mbp, while in Limousin, it showed a more rapid decay. Variation of different LD levels across autosomes was observed in all the breeds. The results demonstrated a rapid decrease in Ne across generations for local breeds, and the contemporary population size observed in the local breeds, ranging from 41.7 in Calvana to 17 in Pontremolese, underlined the demographic alarming situation.
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